[Python] SVD using numpy not returning anything, terminates the program instead [closed]

I have a linear algebra exercise wherein I have to find the inverse of a given matrix using SVD. I made this code utilizing numpy. However, when executed, the code pauses for a long time before terminating early--I know it's terminating early since it does not reach line 11 where I try to print the S values. It also does not reach line 17.

import numpy as np

A = np.array([[[6,0,2],[2,6,5],[9,7,1]],
[[1,6,4],[5,4,9],[6,9,2]],
[[3,5,9],[5,3,7],[8,3,3]]])

ans = np.zeros((A.shape[0], A.shape[1], 3)) # Where A is 3x3x3 array

def svd_inverse(mat):
U, S, V = np.linalg.svd(mat)
print(S) # to test whether or not the is reaching this line
return V @ (S**(-1)) @ U.transpose()

for k in range(3):
ans[:,:,k] = svd_inverse(A[:,:,k])

print(f"Inverse: {ans}")


I already tried solving this using MATLAB and I successfully got the results as seen here in a screenshot. With the live code screenshot here. I already tried searching other forums and posts, reading the documentation, but to no avail. Can someone help me? I'm stuck here for days. Thanks in advance.

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